Intelligent Automation Solutions – 7 Questions to Ask

When it comes to IT operations, there’s no question that it is crucial for organizations to increase their efficiency. In fact, with the ever-growing complexity, service levels and performance, greater operational efficiency becomes not just an option, but a competitive necessity. Intelligent automation solutions can help your IT operations become more efficient, thereby improving your organization’s bottom line.

That being said, not every automation tool is the same. And with so many to choose from, the selection process can be confusing and downright overwhelming. Here are seven important questions that should help you make a more informed decision.

1. What are the integration points? Before choosing your intelligent automation solution, you should first verify that it will have touch points and triggers that integrate with your data center systems, including different OS, legacy systems, integration with help desk such as ServiceNow, monitoring and management systems, etc. The more integrated the better.

2. What should be expected in terms of deployment effort? Evaluate how much time and effort will be required for deployment (setup, configuration, implementation, etc.). You want to make sure that the time-frame proposed works with your organizational needs. Also, set expectations so that everyone is on the same page throughout the process and there are no unexpected surprises.

3. What is the required skill set for this particular platform? Part of the implementation process involves training and adapting to the new system. Before moving forward, you should understand what the estimated learning curve will be for generating automated workflows independently. You’ll also want to determine ahead of time if any scripting will be required. (Tip: Look for a solution that does not require coding or programming required. This enables rapid adoption and time-to-value.)

4. Does this product feature out-of-the-box functionality? Some intelligent automation solutions provide ‘pre-canned’ templates for various commonly performed tasks. If the platform you are considering offers this, the next step is to determine whether these generic templates can easily be tailored to fit your unique business environment and processes. Templates are a great place to start, but the more customizable, the better.

5. What level of human intervention is available? Even the simplest automated processes will require some type of human decision at some point during the process. The question to ask is whether you will be able to embed decision-making logic into workflows for remote decisions on process execution. This allows management to maintain control over the process from start to finish.

6. What kind of scheduling functionality does it offer? While some automated processes will be triggered by system events, others, such as repetitive tasks, will need to be scheduled. You’ll want to make sure the automation platform you select provides for full scheduling capability.

7. Does it take into account regulatory compliance? Meeting regulatory compliance requirements is a critical part of every organization’s success. When evaluating an intelligent automation solution, be sure to find out whether it can help you with these initiatives. For instance, does the tool provide tracking of events, reports and knowledge management that will help the organization comply with regulations?

These are the seven most important things to consider when evaluating automation for your organization. By asking these key questions and understanding what to look for, you will have a much better chance of selecting an intelligent automation solution that will be a perfect fit for your business and ensure project success.

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3 Ways AI is Revolutionizing ITOps

It’s hard to imagine that while just a short time ago, people were asking what AI was all about and whether it was something worth investing in, yet pretty soon we’ll be asking how we ever lived without it. Artificial intelligence and machine learning have radically improved the lives of many, in particular, IT managers, enabling them to optimize their precious time and add legitimate value to their organizations. Here are three specific ways AI is redefining the role of ITOps.

Reduction/Elimination of Time-Consuming Tasks

Each and every day, IT managers are burdened with tasks. Some of those tasks are complex, tedious and mission-critical. Others are menial, mundane and time-consuming – administrative tasks, such as scheduling, setting deadlines and alerts, establishing priorities, directing daily operations, coordinating project activity, managing and analyzing workflow…the list goes on (and on, and on).

Here’s where AI is already making a remarkable impact on the lives of ITOps managers. By shifting most or all of these time-sapping administrative issues to intelligent automation, these leaders are freed up to allocate their skills and expertise to what’s most important. AI is particularly beneficial in terms of managing any process that is repeatable, such as preparing reports (and we all know how much IT managers adore reporting). Many organizations worldwide are already taking advantage of AI’s quantitative data analysis capability to generate analytical reports.

Increased Knowledge/Skill/Judgment Work

Only an IT manager would understand how a so-called promotion can actually be more of a headache and disappointment. Think about it. You’re awesome at what you do – ITOps work – so you get moved up the ladder, into a role that is filled with endless administrative tasks (as mentioned above). Feels more like a demotion than anything else. Many IT managers in this position would much rather be focusing their time, energy and expertise on things like:

  • Developing standards and best practices
  • Overseeing complex workflows
  • Identifying duplication and waste, quantifying outcomes and providing analysis
  • Coordinating and managing operational budgets and initiatives
  • Analyzing data
  • Developing departmental and interdepartmental goals
  • Evaluating proposals to determine requirements and feasibility
  • Consulting with users, stakeholders, technicians and vendors to determine needs and requirements

Artificial intelligence has gifted IT managers with the ability to perform more of the knowledge, skill and judgment work that they love, not only because it frees up time, but because the technology is inherently designed to support enhanced decision-making within ITOps (and beyond). That’s not to imply that human expertise and insight will be replaced by AI. To the contrary, cognitive skills and critical thinking will become even more prevalent because IT managers will have more time.

More Room for Creativity

The flood of demanding day-to-day tasks that ITOps manager face leaves little to no room for the creative thinking that is necessary to drive innovation. Some of the areas where these leaders can add value include brainstorming to improve future IT initiatives, strategizing on organizational goals and objectives, keeping up with tech developments, acting as champion for the IT department, just to name a few.

Integration of artificial intelligence is facilitating more creative thinking by enabling better experimentation and collaboration. When IT managers are able to spend more time strategizing, the human element of creativity will flourish for the betterment of ITOps and the organization as a whole. What’s more, IT managers will be able to take on more advisory roles thanks to AI’s presence. The ability to hone social skills will continue to open up new and exciting opportunities.

Conclusion

ITOps managers across the globe are already experiencing drastic changes with the growing adoption of AI technology. The relief from administrative tasks alone have made it well worth the investment, with the promise of even more widespread benefits that will change the scope of everyday life for the better.  

Want to experience some of these incredible, life-changing benefits for yourself? Give Ayehu a try completely free for 30 full days. Click here to start your free trial today!

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Pros and Cons of IT Chatbots

When IT chatbots were first introduced, admittedly, they were less than impressive. They were slow, clunky and in many cases, it was painfully obvious that a robot was on the other end. Advances in artificial intelligence technology, however, have addressed these concerns and the virtual agents of today are becoming more human-like by the minute. And their popularity is growing, with Gartner predicting that by next year, 50% of medium-to-large enterprises will be using chatbots.

Should you be one of them? Let’s take a look at a few of the ups and downs of using virtual support.

Pros of IT Chatbots

Frees Up Humans Resources – The first and most obvious benefit to deploying IT chatbots for the helpdesk is that it shifts a significant portion of the workload from human to machine. This frees up human agents to be able to focus their high-level skills and cognitive talents on more complex and important business initiatives. This is a much more optimal allocation of resources.

Enables 24/7 Support – Most organizations can’t afford to pay for round-the-clock IT support, and for those that do have the budget, justifying it can be a challenge. IT chatbots are available 24/7, which means if a problem arises at 2am, there’s a good chance it can be automatically addressed and resolved without human intervention. A higher level of support without having to pay live agents? Yes, please.

Advanced Interaction – With the right software solution, IT chatbots can be fully customized. Furthermore, thanks to advanced AI technologies like machine learning and natural language processing, virtual agents can be so “intelligent” that the end-user doesn’t even realize they’re interacting with a robot and not a fellow human.

Cons of IT Chatbots

Volume – The overarching goal of any IT chatbot implementation is to automate routine, manual and recurring tasks. Logically, if the volume of recurring activities for your IT team is low, the benefits of introducing virtual agents may not outweigh the cost and effort it takes to implement.

Time/Resources – While it’s true that chatbots free up existing IT staff, the technology isn’t something you simply plug and play. It requires oversight and maintenance by skilled human workers who can make sure the software has all the information it needs, can add new services, applications and processes for the end-user as needed and that the bots are properly tested.

Fear/Resistance – Lastly, as with most automation technology, chatbots often elicit feelings of fear and resistance from human workers who may be concerned that they are being replaced. Additionally, if the technology is not up-to-par, the end user may push back against the idea of working with virtual agents vs. human help desk support.

These issues can be overcome, provided the right people, technologies and policies are in place. In fact, if you take your time to fine-tune your chatbot platform, it can easily become an effective and realistic channel for supporting end-users, making it well worth the time and investment.

Get started today by laying a strong foundation. Try Ayehu FREE for 30 days. Click here to download.

How (and why) to run your in-house IT like an MSP

For decades, businesses have been turning to MSPs to handle their day to day IT needs. This outsourcing was something that many small to mid-sized companies were forced to do, since housing IT internally wasn’t always an option. The good news is, technological advances have begun to make it possible for companies of any size to affordably manage IT operations in-house – and with the same efficiency and service levels as an MSP.

We’ve written countless posts about how tools like intelligent automation can be leveraged by MSPs to save time and reduce costs. This same concept can be applied to internal IT departments as well. For small to mid-sized businesses that previously relied on external MSPs to essentially serve as their IT office, the reason was typically budget. It was simply more cost-effective to outsource IT rather than to manage it in-house. But with the ability to accurately measure the value of internal IT, more and more smaller companies are recognizing the benefits of keeping things on-site.

The answer to the age-old question of how an internal IT team can match the efficiency of a managed service provider lies in automation. When you are able to automate not only individual repetitive tasks, but entire complex workflows, suddenly the idea of running a busy IT operation doesn’t seem as overwhelming. You no longer face the need to hire more staff than you can afford, and those team members that you do employee will have the ability to focus on critical things that require a human touch, such as analyzing and developing business strategies for future success.

Benefits of Using IT Process Automation to Keep IT In-House

While using MSPs is certainly not a bad option, there are a number of specific benefits that a business can realize by keeping IT in-house. These benefits include:

  • More Control – Outsourcing always requires giving up a certain amount of control. Keeping IT operations internal gives the business full control over all processes and procedures.
  • Flexibility – A quality intelligent automation platform provides flexibility and customization to each business’s unique pain points. That means that your internal IT can be designed specifically for the needs of your organization, unlike an MSP which can only adapt so much.
  • Higher Level of Security – It goes without saying that internal versus outsourced departments always provide a more secure atmosphere. IT operations for industries that deal with more sensitive information, such as the financial sector, benefit greatly from keeping all transactions in-house.
  • Saves Time – Internal IT operations eliminate the need to contact and rely on a third party for support requests, which can save time. The beauty of automation is that it is designed to make IT operations more efficient, so it is inherently a time-saver. Couple this with the fact that intelligent software is doing the heavy lifting, freeing up personnel to be available if and when an issue arises, and you’ve got a highly effective and efficient department that is able to maintain exceptional service levels.
  • Saves Money – Keeping IT internal saves money over time, since you will no longer need to incur the costs of outsourcing to an MSP.

Think your business is too small or lacks the resources to manage IT operations in-house? Think hiring an MSP is the only option? Think again.

With technological advances, namely the rise of intelligent automation, now organizations of any size have the ability to achieve the same operational efficiency with their in-house IT as they would with a Managed Service Provider.

Still not convinced? Take our Next Generation IT Automation platform for a test drive FREE for 30 days. Click here to claim your free trial.

Episode #13: The Gold Rush Being Created By Conversational AI – Cognizant’s Matt Smith

March 15, 2019    Episodes

Episode #13: The Gold Rush Being Created By Conversational AI

In today’s episode of Ayehu’s podcast we interview Matt Smith – Conversational AI Practice Leader & AVP of Cognizant.

Less than 10 years ago, having intelligent conversations with a voice-enabled computing device was a familiar feature of Sci-Fi movies, but an uncommon sight in everyday life. A decade onward all that’s changed because as we’ve seen time and time again, there’s no such thing as science fiction, only science.  Wherever you look these days, smart speakers, chat bots, and other advanced communication channels employing conversational AI are making information more accessible than ever.  Adoption of these technologies is so rapid in fact, that it appears to be hastening the demise of mobile apps, and will perhaps eventually become our primary application interface in the not too distant future.

To better understand this seismic shift in how organizations interact with their customers, employees, and partners, we turn to Matt Smith, Conversational AI Practice Leader & AVP of Cognizant.  Matt shares with us some of the fascinating use cases he’s seen companies deploy, as well as where he thinks conversational AI will go over the next 3-5 years.  Along the way we’ll find out what use cases are best suited for conversational AI, key factors in creating a successful conversation design, and how conversational AI could even change the way you order fast food in a drive-thru.




Guy Nadivi: Welcome everyone. Our guest today on Intelligent Automation Radio is Matt Smith, Conversational AI Practice Leader and AVP of Cognizant.

Matt has had an illustrious career in robotics process automation, and IT outsourcing. He’s served on the leadership board of the International Association of Outsourcing Professionals. And as an industry leader, in the field of conversational AI, we wanted to get his perspective on this disruptive technology, which is really taking a number of industries by storm right now.

Matt Smith, welcome to Intelligent Automation Radio.

Matt Smith: Thank you very much, Guy. It’s a pleasure.

Guy Nadivi: Matt, you run Cognizant’s conversational AI practice. Can you speak a little bit about what is conversational AI, and differentiate it from the other AI we hear about out there?

Matt Smith: Yeah, of course. The way that the term is generally used right now, conversational AI, it actually refers to a number of different ways for brands to build a new way of engaging with their customers. Their customers could be internal workforce, it could be actual customers of theirs that are already buying something from them, it could be prospects. But conversational AI has become an umbrella term for everything that could be, for example chatbots, or intelligent speaker devices, or hands-free speaker devices, virtual agents, and even more and more examples of conversational AI we’re seeing are applications within a vehicle, or in locations within a home where you can speak your instructions to a device, versus a traditional way of using a keyboard or some other form of interaction.

Conversational AI, it really is a subset though of the broader category of artificial intelligence technologies. You can’t do true conversational AI without a couple of the key building blocks that are part of AI systems today. Natural language understanding is a critical component of a conversational AI solution. Machine learning is a very important component of conversational AI. Those are really part of the engine, if you will, that makes these technologies able to do what they do, and seem very seamless from an end user’s perspective.

Guy Nadivi: You mentioned that it’s a replacement for keyboards, and you’ve described conversational AI as hands-free computing or screenless computing. I think most people personally experience conversational AI when interfacing with a chatbot, or intelligent speakers like Amazon Alexa. For organizations that have implemented conversational AI for their customers, how have you seen that it’s given them a competitive advantage today?

Matt Smith: If you look at some history examples of where a new user interface has emerged, and that’s really if you think of the idea of screenless interface, or screenless computing, it’s a new user interface. If you look back in some past eras, we had the website era in the ’90s, and companies – initially it was seen as a research tool, or it was seen as an extension of branding, and a lot of companies just took their brochures and converted them to websites. But eventually got to a point where they realized, there’s a lot more here and customers are interested in doing a lot more than just flipping through something electronically that they could previously have done with a catalog. Much the same happened a decade later with mobile apps. Then it was a little bit of a similar experience where companies then just took their websites and converted that to a mobile app.

But in both those cases, a learning curve happened where the idea of these new user interfaces started to catch on with marketing departments, with sales organizations, with customer services teams as a new way to compete for customers, as a new way of differentiating what they can represent to their marketplace. I think we’re seeing that very much play out now with conversational AI, Guy, where people are experimenting with the technologies, and very quickly starting to learn that this is a new way to differentiate in the marketplace.

The whole idea of conversational AI is to create a better ease of use, a greater convenience for customers, the idea of personalization, and being contextual to a situation is very much a part of it. Again, that’s where some of the AI technologies come into play, but it’s the new competing space for brand differentiation, is really what conversational AI has become.

Guy Nadivi: In broad terms, what are some of the lowest hanging fruit best suited for conversational AI applications within an organization?

Matt Smith: Well there’s three that we see right now, Guy, with the clients that we work with. The first is if you think about very high frequency, highly repetitive informational kinds of requests. Things like frequently asked questions that today might be on a website location or embedded within an app, finding forums, and finding locations or branches, or store sites, or looking up menu items. Those kinds of very high frequency, highly repetitive kind of interactions, that’s one area that we see a lot of organizations starting with first.

As far as some of the use cases, lead development and lead conversions is definitely an area of focus for a lot of conversational AI solutions. As a way of reaching out across a multitude of channels, and engaging where your customers are, or where they would prefer to engage with you is a great place to look for conversational AI low hanging fruit or early opportunities.

The third area is lower complexity but transactional inquiries. It’s a step up in complexity from just information requests, and it will typically require some kind of login, or credentialing, or authentication of some sort. But for example, being able to look up an account balance, or update missing miles on an application, a mileage app for an airline, filling in applications, or initiating the ordering of products, those kinds of today, fairly simple transactional activities are also become more and more popular for companies that are looking to implement conversational AI.

Guy Nadivi: To refine that a little bit further, can you please share with the audience some of the more intriguing use cases where you’ve seen conversational AI impact an organization’s operations?

Matt Smith: The main area of focus right now for most enterprise kinds of clients, Guy, is in the idea of contact center transformation. If you think about the way contact centers had evolved over the years, and all the elements of technology today that exist, and some of it has been very beneficial for customers, and some of it customers we all have come to despise, the IVR or having to repeat your account number every time you get transferred to someone else. Those are areas where organizations are focusing today on conversational AI, and again, how can it create a better customer experience versus the ways that organizations have used some of these other technologies? We see a lot of activity in contact centers, and it could be voice interface, it could be better versions of web chatbots, it could be an integration of those technologies, it could be intelligent messaging as an option.

We were working with one client, and they actually started to experiment, Guy, with the idea of offering customers that were on hold, the option to try and resolve the question themselves using a messaging solution. They didn’t have to download an app, they didn’t have to go to a website. It would embed a functionality within their existing messaging app on their mobile device, and they had an 80% acceptance rate of customers that chose that option to self-serve rather than waiting on hold for the next available agent, and were able to resolve their own issues. Those kinds of ideas, I think, are really gonna start to catch on over the next 12 months or so.

Then some of the other areas that I think are more from a user-oriented perspective that we’re gonna really start to see a lot of examples, so we’re doing some work in the fast food industry. If you think about the way drive-thrus work today, it’s a very linear process. You wait in line in your vehicle to pull up to the sign, you tell the operator on the other end what you’d like, they read it back to you, they tell you what you owe, you pull up to a window. It’s not really ideally for the customer or for the restaurant because they can only sell as much traffic as they can run through the drive-thru. The ability of conversational AI to really extend the footprint of the drive-thru concept, but be able to leverage that around vehicles that could be anywhere in the area to place orders, and to do it not necessarily through a person, but to be able to order their items or their meals through conversational AI, and then just pick it up if they get anywhere near the building, another cool use.

Then we’re seeing, for example, in retail environments. We’ve all been in stores, grocery stores, or big box stores, or big hardware stores, and you simply can’t find the item you’re looking for. We’re helping a couple of companies that are operating in the grocery space to put intelligent agents on top of their mobile app. You can simply ask where an item is located, and not only does it tell which aisle and which shelf, but it can bring up a visual representation. As you get closer, it uses echolocation to show you exactly where your item is gonna be. I think those are some of the things that we’re seeing right now are really gonna be, before much longer, just standard for a lot of the interactions that we have.

Guy Nadivi: I love that last use case, especially at Costco where they change things every week. I could use that right now.

Matt Smith: We all could. Think of the time it would save you and the convenience too.

Guy Nadivi: Matt, in a recently published article, you state that, “Conversational AI is a top 2019 priority on the strategic plan for nearly every company we’ve talked with.” Is this an indication conversational AI has crossed the chasm from innovators and early adopters, and is now being embraced by the early majority to become a mainstream technology? Or is it still somewhat experimental?

Matt Smith: Yeah, it’s straddling those areas. I think it somewhat depends on the industry, Guy, because there are certain industries where it’s somewhat easier to implement. For example, the technology can be used equally in a retail environment to do simple transactions, like we talked about earlier, or in a healthcare environment. But if you put on top of the healthcare environment the complexities of security, and privacy, and compliance that exist, it suddenly makes it potentially a lot more complicated, so the functionality could be there, but there’s other drawbacks that make it more challenging.

What that means is we’re seeing certain industries move faster with conversational AI-based solutions than others, but there’s definitely this effect from a customer point of a view, a consumer’s perspective. If I can use this technology in a certain way over here, why can’t I use it the same way over there? It’s pushing the whole pile forward. I think it is creating this … We’re crossing over into the next era.

We think that we’re in this, what I would call the third microphase, or the third phase of conversational AI. It really is now about this idea of starting to put more and more focus on a multitude of ways to engage, connecting these projects, and having a strategy for scale. I think we are at that point, and just if you look around, all the examples you see as a consumer of conversational AI coming into play, I think we can all sense this has happened.

Guy Nadivi: Is there a single biggest factor driving adoption of conversational AI among your clients?

Matt Smith: Yes, there is. It’s really two dimensions. The drivers are the idea of commerce and customer care. Using these technologies can extend, or enhance, or improve the idea of both commerce within customer care and customer support. That’s one dimension as the driver. Then the other is really a need for scale and for strategy.

Again, I’ll draw a parallel to where websites were in the ’90s. When they first started to gain a degree of popularity, there were a lot of companies at the time that said, “What do I need a website for? That’s for such and such, a kind of brand, or for that kind of an example or a use. We don’t need a website, our customers wouldn’t go there.” Then suddenly those same companies found, in many cases they had hundreds of websites that had popped up as different teams around their organization were experimenting with this technology, then they were building little, today we would call them microsites, but building little websites for their department, or their function, or their operation. That’s when this idea of scale and strategy suddenly hit IT leaders, and brand and marketing leaders. Back then they said we need brand standards, we need the architectural standards, we need strategies for security.

That’s what’s happening right now with conversational AI. We’ve had these two earlier phases of a lot of experimentation, and a lot of small pilots, and small deployments. Now suddenly the IT leadership, marketing leadership, chief digital officers are all stepping in and saying, ‘We have to get our arms around this quickly and have a good, smart strategy for how we’re gonna to go about it.’

Guy Nadivi: I read in 2017 that Gartner predicted a couple of developments that I think many people in our audience will find startling. They forecasted that, “By 2019,” this year, “20% of brands will abandon their mobile apps,” and, “By 2020, 40% of all mobile interactions will be via virtual assistants,” which I think of course means conversational AI, or at least partially conversational AI. Matt, my question for you is, have we reached peak app and started transitioning towards conversational AI as the predominant user interface going forward?

Matt Smith: I think if we look … Two years ago, making this prediction, I think it was a realistic way to look at the way things were trending. I would flip it around today though, in the middle of this first wave that Gartner was predicting. I don’t know that it’s the brands are necessarily abandoning their apps, it’s that the users and customers are looking for alternatives to apps. We’ve all seen the stats of how many unused apps everybody has on their phones, or their tablets, how much functionality within a given app people never even are aware exists, much less take advantage of. I think users have just reached app fatigue, and they’re looking for or hoping for a better way to engage.

You parallel that with the use of messaging as a preferred way to communicate for a variety of situations. Certainly a generational or demographic trend favors messaging for lots of users. But even in the case of, like I talked earlier about that contact center scenario, where users of any demographic were given the choice on their own to opt into a messaging approach, versus waiting online, or maybe fumbling through the mobile app. The uptake was 80% to shift to messaging. There’s plenty of data now showing that messaging is becoming rapidly the predominant way for engaging with customers in this asynchronous method. I think we are seeing that really start to play out.

As far as calling conversational AI the dominant user interface, I don’t know that I would say it’s gonna become the dominant interface. I think it’s gonna be one of the primary ways that people will interact with technology going forward. We’ll look back on this 25- or maybe 30-year era where the way you would get information into or out of technology was with a keyboard, and then a mouse, and then a touchscreen. We’ll look back at that and say, “Well boy, that was clumsy.” Much like we look back at blackberries today and go, “That was the way you would send a message?” And we chuckle about it, but it’s in hindsight.

I think conversational AI will be the same in some situations where it does become predominant for certain uses where it makes the most sense. In other cases we’ll see other forms of probably AI-driven user interfaces emerge as dominant in those eras.

Guy Nadivi: Do you think conversational AI can eventually extend beyond traditional computing devices? Could we see voice enablement eventually found in everyday things like product packaging?

Matt Smith: You don’t have to go any further than the Consumer Electronic Show this year. CES in January 2019 was all about conversational AI. It wasn’t always called that, but that’s what was the dominant theme across CES.

It’s happening now. Whether it’s in home, all the ways that you can drive your home automation, or home security, or air conditioning and heating systems, or lighting is voice controlled in more and more situations. Or you look inside of vehicles and the idea of avoiding distracted driving using voice assistants for everything, from navigation to selecting the media that you listen to on the dash, to conducting basic transactions perhaps on like we talked about earlier, information requests, or placing orders for fast food on your way to work or to run an errand. We’re seeing conversational AI happen there.

Then in workplace solutions. There’s going to be more and more examples of voice replacing other forms of interaction. If you think about the way most of us would get into an office building today, where we would go to work, you swipe your badge. Well that could easily be replaced with voice identification instead of having to tote the badge around, or looking up the information in the conference room, for example, and connecting to all the systems. We’re putting those solutions in place for clients today.

In healthcare there’s lots of examples of voice automation starting to make its way into patient rooms, or even operating rooms, or labs or clinical environments where you want to be able to operate without your hands, where you want to engage with the patients, or you want to maintain a sterile environment. We’ll see lots of those kinds of big examples too become more and more prevalent as voice starts to make its way. The idea of extending the untraditional computing is happening really fast.

Guy Nadivi: Matt, you’ve talked about some amazing advancements today, but AI and automation sometimes frighten people from a job security standpoint. What are some ways you think conversational AI will make employees more valuable to their organization?

Matt Smith: Well it definitely does, but I think it’s interesting that the term AI by itself for a lot of certainly popular media, it’s this dark robotic future, and it speaks about the presence of these robots everywhere, and job loss, and loss of control and personalization. But when you put the word conversational in front of AI for just about every situation, it seems like it becomes a much friendlier situation.

I think we see lots of examples, Guy, where the idea of conversational AI makes a workforce far more productive and able to do things that are much more meaningful and enjoyable, just like if you look at intelligent automation. What that’s been able to do with very menial tasks like data entry, or screen scraping, or mouse clicking between forms, conversational AI can automate much of those same kinds of processes. The difference is, in a lot of cases, intelligent automation or earlier forms of RPA required very structured rules-based processes, and structured forms, and structured data. Conversational AI can exist in a world where there’s not as much structure to the process. It’s natural language versus structured language, and so it gives us more flexibility and creativity.

But we’re seeing lots of examples. Back to the contact center scenario, conversational AI can be just as beneficial for a contact center agent to deploy in the background of supporting a customer so they can anticipate better what the right response or the right answer is to a question, or they can have a conversational AI system working in the background, pulling up information for them, or pulling up data that’ll help them provide a better solution while they are talking to the customer and understanding exactly what it is that they need or what challenge they’re facing.

Those are some of the examples. If you think about the insight and the analysis that conversational AI can start to open up for organizations, because if it’s hard, it’s a significant amount of data. Within that data is often times it’s better solutions for customers, it’s faster resolution, or it’s a quicker identification of the right product or service that somebody needs. We see that working in tandem now with a lot of workforces.

As customers, we may not even know that there’s a conversational AI system side-by-side with the agent we’re talking to, but increasingly it’s there, as part of the background supporting them.

Guy Nadivi: Now you mentioned structured and unstructured processes, and at Cognizant, you’ve developed some best practices for conversation design. Can you expound a bit on what factors differentiate a successful conversation from one that leaves customers frustrated?

Matt Smith: Yeah, there’s a few that we think are really important upfront. One of the early lessons that we learned, if you look back a couple years ago when conversational AI was just getting started as a business idea, it was usually technology first, and customer expectation much later in the process. One of the things that we stress is you have to start first with what is it that your customer wants to do, or where do they want to engage, and what are their expectations from a conversational AI solution. That’s one. The data availability for training the solution is critical. You could have with my team, on the surface a really cool use case, but if you don’t have the data to train the ML, if you don’t have the data to enable the chatbot, or the voice assistant to have a deep and broad enough data set to reference against, it won’t be a good solution.

Another key factor, Guy, is what applications in the backend of our enterprise will we need to have access to, and how easy or how complicated will it be to connect a conversational AI system to these backend applications that run our warehouses, or run our inventory systems, or run our invoicing and billing, or run our customer care? Those backend enterprise apps are still driving the organization, so you have to connect to them.

Then finally, I mentioned early, in certain context and particular in certain industries, you have to have a discussion around security and privacy at the very front of the project, and makes sure that that’s not something that gets neglected, or passed over until you’ve done too much work, and then you’ll find that you’ll have to do a lot of backtracking. Those are some of the real key factors that we see.

Guy Nadivi: At this point in the evolution of the conversational AI market, there’s multiple consumer platforms like Apple Siri, Google Assistant, Amazon Alexa, etc. Do organizations have to conduct separate development efforts for each platform, or is there a common API they can write to?

Matt Smith: The answer is that there’s parallel work efforts that will have to happen as organizations look into addressing different devices or different brands. Today, that’s simply one of the limitations or challenges of implementing conversational AI. It’s an important factor because again, it comes back to where are your customers? Not everyone uses Siri, not everyone uses Alexa, not everyone uses Google. Some homes have a multitude of those devices, others are built around just one, and some people don’t use them at all, they prefer to use messaging or chat.

The point is, you have to have really a multi-device strategy, a multichannel strategy, and increasingly with conversational AI, a multi-modal strategy. If you think about some of the newer voice interface devices where it’s not just an intelligent speaker, but there’s some images that are included as well, Echo Show or Google Home Hub are great examples on the consumer side where it’s multi-modal now. Voice-driven, but you have the ability serve up and show content.

Some of the work is reusable. Certainly the strategies are reusable. Customer expectation, that kind of work is reusable, but when you get down to a code level, often times you’re going to be coding for different channels, different devices. And like mentioned, certainly different ways or different modalities of interface. You have to think through all of that before you undertake a project.

Guy Nadivi: Could be a great market opportunity for someone to come along and….universal interface for all of the …

Matt Smith: Yeah. Well, and that’s a good point. I think we’re going to start to see, maybe not on the coding side right away, but from a user’s perspective, we’ll have the lessons learned from the way consumers are looking at these technologies too. Eventually they’ll say, “Well I don’t want all these different. I just want my favorite virtual agent, so my agent will drive all these other different technologies or interfaces.” I think we will see some of this start to simplify itself from a consumer perspective for sure.

Guy Nadivi: What are some of your predictions for conversational AI over the next three to five years?

Matt Smith: There’s really three big predictions, or three things that I think we’re in fact seeing them happen right now. One is virtual agents will become the preferred interface versus apps. Whether it’s Siri, Google Assistant, Cortana, your virtual agent will be increasingly personalized to you, and to how you go about your day, whether it’s your work day, or your personal day. That virtual agent will engage initially with the apps on your behalf, but at some point I think we’ll see a crossover where virtual agents will engage with other virtual agents or directly with systems. The app will fade more and more into the background, and maybe become just a specialized tool.

The next is, as far as big trends, is the idea of contextualization of the process. That’s where the capabilities of AI, and all these super computing solutions really come into play, and we see it today. We hear examples of people say, “I got in my car and Siri popped up and said, ‘It’s gonna take you 25 minutes to get to the office today,'” and you go, “Wait a second. How did it know I was gonna go to the office?” Well it’s contextual. It’s running in the background and it knows that on Monday through Friday, Guy gets in his car at 7:00 a.m., and he goes to work, and it knows where you start and where you stop. Increasingly, it’s telling you, “Well look, today there’s construction. You need to go a different way.” I guess contextualization is gonna become more and more accepted and expected.

Then the third is we’ll see conversational AI everywhere. In a sense, we won’t see it at all because it will become more and more transparent. The idea of voice interfaces will just be the way that we engage, whether it’s with our technology, or our homes, or our vehicles, and even in our workplace. It’ll just become part of the backdrop of how we engage. Contextual, everywhere, and virtual agents I think are three trends to really watch for.

Guy Nadivi: For the enterprise IT managers, who have never dealt with conversational AI, what should they know before deploying it?

Matt Smith: Steve Jobs probably has the most appropriate quote, and he was talking for a different era, but I think it applies really well here which is you’ve got to start with the customer experience and work backwards towards the technology, not the other way around. I think a lesson that we would impart to, whether it’s IT leadership, or marketing leadership, or brand digital officers is just that. Focus on the customer first. That’s one.

Link your projects as much as possible, which means for leadership, bring together different teams, business teams, IT teams, cross functional groups that all will have their perspective on where conversational AI can come into play. Again, think beyond the idea of chatbots. Most companies, I think, are today thinking past the point of a website, text-based chatbot, and think about other ways that you’re going to be using conversational AI. Again, it’s that omni-channel, multi-device, multi-modal future that is becoming the new user interface.

Another important point I think is look for innovation partners that can help not just from a project delivery perspective, but also in terms of supporting the strategy of how these technologies are being deployed, and where they’re going, and can help think about the road maps that should be built along the way. You’ll save a tremendous amount of time if you’ve got those right partners in the front end, and I think you “de-risk” your projects in many ways by doing that with partners that can help from an innovation perspective, as well as do, call it basic deployment capabilities.

Guy Nadivi: Matt, you speak with customers all day long about conversational AI. What is the one take away piece of advice you have for CIOs, CTOs, other IT executives considering or already deploying conversational AI in their environments.

Matt Smith: I’ve said it several times, I think, but it’s really the voice of the customer. The projects we’ve seen, Guy, that have the best success started with the customer, not just thinking about, but talking to customers, and looking at data of past customer interactions, and testing out in really small MVP, so Minimal Viable Project or Product approaches before trying to scale and get too complex. Customer first, and go bite-sized pieces, very short spread, and iterate as you go. Those are where the companies that we work with have followed that plan. They have very good success. When they don’t, they’ll see the adoption just isn’t what they expected, or even worse, the reaction from customers is to let them know on social media or other places that they hate their new chatbot. If you start voice of the customer, I think you’re gonna be very well served in this new user interface era.

Guy Nadivi: I think that’s excellent advice, even outside the realm of conversational AI.

All right, looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Matt Smith, thank you very much for joining us today, and sharing your thoughts about the current state of conversational AI. We’ve really enjoyed having you as our guest.

Matt Smith: Guy, I thoroughly enjoyed it, and look forward to talking again.

Guy Nadivi: Matt Smith, Conversational AI Practice Leader and AVP of Cognizant. Be sure to get in touch with Cognizant to learn more about their services.

Thank you for listening, everyone, and remember, don’t hesitate, automate.



Matt Smith

Conversational AI Practice Leader & AVP of Cognizant.

Matt is responsible for Cognizant's Conversational AI practice, a team dedicated to helping companies understand, prepare for and benefit from a new class of technologies leveraging advances in cognitive computing and artificial intelligence.  Before Cognizant, Matt was a practicing entrepreneur, first launching a company providing sales and marketing programs for outsourcing companies, and later a firm delivering RPA (robotic process automation) consulting for BPOs.  Earlier roles were as sales VP and alliance sales with BancTec (SourceHOV), sales AVP and marketing director at CompuCom, and sales executive with TRW/Vanstar and NYNEX Business Centers.

Matt authors a blog on digital enterprise, intelligent automation and B2B sales and marketing and has published articles for LinkedIn, the Digitally Cognizant blog, Pulse Magazine, Outsourcing.com and Global Services.  He is a regular presenter at Cognizant’s client events including Community and Health Care Conferences, and outside events including the AWS ReInvent, Google Next, AI Summit, the Outsourcing World Summit, the Dallas CEO Exchange and the Outsourcing Institute Emerging Technology Forum. He has served on the leadership board of the International Association of Outsourcing Professionals for both the Tools and Technology chapter and the Robotic Process Automation chapter (the latter he helped launch).  He has also been a member of the Marketing Automation Software Advisory Board, founder / co-chair of Dallas Social Media Breakfast and chair for the Outsourcing Institute’s Road Show Series.

Matt Smith can be found at:

E-Mail:          matt.smith@cognizant.com

Twitter:        @_MatthewJSmith

LinkedIn:     https://www.linkedin.com/in/matthewjsmith01/

Blog:            https://www.matthew-j-smith.com/

Quotes

“The whole idea of conversational AI is to create a better ease of use, a greater convenience for customers, the idea of personalization, and being contextual to a situation is very much a part of it. Again, that's where some of the AI technologies come into play, but it's the new competing space for brand differentiation, is really what conversational AI has become.”

"…we're seeing certain industries move faster with conversational AI-based solutions than others, but there's definitely this effect from a customer point of a view, a consumer's perspective. If I can use this technology in a certain way over here, why can't I use it the same way over there? It's pushing the whole pile forward.”

“We think that we're in this, what I would call the third microphase, or the third phase of conversational AI. It really is now about this idea of starting to put more and more focus on a multitude of ways to engage, connecting these projects, and having a strategy for scale.”

“We've had these two earlier phases of a lot of experimentation, and a lot of small pilots, and small deployments. Now suddenly the IT leadership, marketing leadership, chief digital officers are all stepping in and saying, ‘We have to get our arms around this quickly and have a good, smart strategy for how we're gonna to go about it.’ “

“There's plenty of data now showing that messaging is becoming rapidly the predominant way for engaging with customers in this asynchronous method.”

“Conversational AI can exist in a world where there's not as much structure to the process. It's natural language versus structured language, and so it gives us more flexibility and creativity.”

“As customers, we may not even know that there's a conversational AI system side-by-side with the agent we're talking to, but increasingly it's there, as part of the background supporting them.”

“Steve Jobs probably has the most appropriate quote, and he was talking for a different era, but I think it applies really well here which is you've got to start with the customer experience and work backwards towards the technology, not the other way around.”

About Ayehu

Ayehu’s IT automation and orchestration platform powered by AI is a force multiplier for IT and security operations, helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure. Trusted by hundreds of major enterprises and leading technology solution and service partners, Ayehu supports thousands of automated processes across the globe.

GET STARTED WITH AYEHU INTELLIGENT AUTOMATION & ORCHESTRATION  PLATFORM:

News

Ayehu NG Trial is Now Available
SRI International and Ayehu Team Up on Artificial Intelligence Innovation to Deliver Enterprise Intelligent Process Automation
Ayehu Launches Global Partner Program to Support Increasing Demand for Intelligent Automation
Ayehu wins Stevie award in 2018 international Business Award

Links

Episode #1: Automation and the Future of Work
Episode #2: Applying Agility to an Entire Enterprise
Episode #3: Enabling Positive Disruption with AI, Automation and the Future of Work
Episode #4: How to Manage the Increasingly Complicated Nature of IT Operations
Episode #5: Why your organization should aim to become a Digital Master (DTI) report
Episode #6: Insights from IBM: Digital Workforce and a Software-Based Labor Model
Episode #7: Developments Influencing the Automation Standards of the Future
Episode #8: A Critical Analysis of AI’s Future Potential & Current Breakthroughs
Episode #9: How Automation and AI are Disrupting Healthcare Information Technology
Episode #10: Key Findings From Researching the AI Market & How They Impact IT
Episode #11: Key Metrics that Justify Automation Projects & Win Budget Approvals
Episode #12: How Cognitive Digital Twins May Soon Impact Everything

Follow us on social media

Twitter: twitter.com/ayehu_eyeshare

LinkedIn: linkedin.com/company/ayehu-software-technologies-ltd-/

Facebook: facebook.com/ayehu

YouTube: https://www.youtube.com/user/ayehusoftware

Disclaimer Note

Neither the Intelligent Automation Radio Podcast, Ayehu, nor the guest interviewed on the podcast are making any recommendations as to investing in this or any other automation technology. The information in this podcast is for informational and entertainment purposes only. Please do you own due diligence and consult with a professional adviser before making any investment

MSPs: How to Cut Costs in 4 Easy Steps

We’ve come a long way since the antiquated automation tools introduced at the turn of the century. Huge, clunky and far-from-perfect, those old tools were enough to get the job done, but thankfully have been vastly improved over the years. Now, automation is intelligent, offering sophisticated solutions in easy-to-use, out-of-the-box products that are affordable and scalable.

Yet, to truly get the most out of intelligent automation – particularly if you are in the highly competitive field of MSP, there is still work to be done. Here are 4 key steps to manage your services in a way that is more efficient and cost-effective.

Stay Proactive – Of course you know what to do in the event that one of your clients’ infrastructure is compromised, but wouldn’t it make more sense to stay one step ahead of the game? That way, instead of having to waste time, resources and money putting out fires, you could resolve issues before they developed into serious problems.

Let’s take the task of patch management for example. If you’re handling this manually, vulnerabilities in the days following a new release could be placing your clients at risk and making your job much more complicated than it has to be. Intelligent automation, on the other hand, allows you to take a proactive approach to patch releases, speeding the process and reducing risk.

Develop and Implement Standards – By developing a check list of technology standards that can be applied across multiple devices and clients, you can remove much of the guesswork from the trouble-shooting process. This will improve customer service levels and streamline your own internal operations.

For instance, you can create a list of back-up and anti-virus processes, recommended amounts of memory, standard applications and configurations, etc. You can then automate the process of auditing these standards accordingly.

Manage Policies – In addition to common standards, there are also a number of policies that must be managed properly, particularly in terms of IT usage governance. It’s critical to ensure that all users remain in compliance with the policies of your customers.

Common policy areas include password refresh, application usage, allowable downloads and access security. By setting up a policy management plan that is proactive and automated, you can prevent unwanted actions and reduce the number of tickets you and your team will have to field.

Review Regularly – While implementing the three steps listed above will dramatically improve productivity and performance, you’ll never get your incoming trouble tickets down to zero (nor should you want to). By reviewing your existing tickets regularly, however, you can effectively identify other areas where automation could help.

What pain points are regularly causing you problems that you might be able to streamline for better results? You may also find through routine reviews that adjusting your standards and policy management in certain ways could further reduce the excess workload that your team is currently carrying.

As any MSP, you’re probably struggling with the need to do more with less. As IT issues become more and more complex, the ability to stay on top of the needs of your clients without having to increase expenditure will be critical to your future success. Intelligent automation, along with these 4 key steps, can help position you right where you need to be to stay out on top.

IT Process Automation Survival Guide

Ayehu Launches Automation Academy, Propelling Technology Innovation in Artificial Intelligence

The AI-Powered Automation Future Creates New Opportunities and Demands New Skills

San Jose, CA –- March 14, 2019 Ayehu, a leader in intelligent automation, today launched its Automation Academy to provide IT and security technology professionals with up-to-the-minute knowledge, experience and tools necessary to compete in the rapidly transforming and increasingly AI-driven world.

According to industry leading analyst firm Forrester Research, while 16% of jobs will be lost over the next decade as a result of artificial intelligence and technology, 13.6 million new jobs will be created during that time. Another recent study by Deloitte revealed that while 800,000 low-skill jobs were eliminated by AI and automation technologies, 3.5 million new, higher paying jobs were created.

“Automation and AI are impacting our world every day, and companies are realizing that if they don’t act now they will quickly be left behind,” said Peter Lee, Vice President Customer Experience, Ayehu. “Our dedication to intelligent automation has earned us a reputation as an expert, so we created the Automation Academy to support all those that want to re-educate and re-invent themselves for the future.”

Ayehu’s Automation Academy demystifies automation and gives companies the power to transform, advance and compete in this new environment where traditional approaches to IT and business operations no longer suffice.

The Automation Academy offers an Essentials Package, Advanced Package and online certifications, depending on business needs. Courses are designed to help IT professionals comprehend and cultivate practical automation skills through a variety of interactive learning activities. Training options are flexible to help students get started on the journey from basic to breakthrough.

Ayehu Academy will offer the following courses:

Essential Training

  • Introductory training designed for beginner-level users starting to explore and use automation.
  • Self-led, online module guides students through the fundamentals of Ayehu’s Next Generation Intelligent Automation and Orchestration Platform.
  • Explore theoretical concepts and participate in hands-on exercises to build a foundational understanding of automation technology.

Advanced Training (includes Essentials)

  • In-depth training on how to become the future of intelligent operations, including the ability to plan and build automated workflows.
  • Receive expert instruction either online or on-site for small or large audiences.
  • Formal certification awarded upon successful course completion.

Online Exams

  • Exams to test automation technology knowledge, assess in-depth awareness and verify student skill level.
  • Flexible online availability for anywhere, anytime testing.

Ayehu’s AI-powered Next Generation Intelligent Automation Platform is the cornerstone for the academy. The platform incorporates artificial intelligence to augment human ingenuity, in order to enable the creation of the next generation of intelligent applications. It delivers no-code, automated workflows that help enterprises save significant time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure.

“We’re excited about the overwhelmingly positive response we’ve had already. Many tell us they ready to go all in on training, and some are planning to establish internal automation centers of excellence. Embracing automation will create opportunities for promotions and new positions, and most importantly give people the freedom to be true innovators,” concluded Lee.

To learn more about the Ayehu Automation Academy and the company’s Next Generation Automation and Orchestration Platform powered by AI, click here.

About Ayehu

Ayehu’s AI-powered automation and orchestration platform is a force multiplier for IT and security operations, helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure. Trusted by hundreds of major enterprises and leading technology solution and service partners, Ayehu supports thousands of automated processes across the globe. For more information, please visit www.ayehu.com and the company blogFollow Ayehu on Twitter and LinkedIn.

5 Things Driving AIOps

Thanks to the forces of digital transformation, IT operations is undergoing some pretty significant changes. Traditional IT management techniques are becoming obsolete and an entire restructuring of our IT ecosystems is underway. In response, IT operations leaders are using artificial intelligence to help them do their work better, faster and cheaper. Gartner has coined a term for this fundamental shift. It’s known as Artificial Intelligence for IT Operations, or AIOps for short.

AIOps addresses the challenges of speed, scale and complexity that IT leaders are facing in the wake of digital transformation. Here are five specific factors that are driving forces behind AIOps.

Manual Infrastructure Management – Today’s IT environments are a mishmash of SaaS integrations, third party services, mobile, managed and unmanaged cloud and more. Traditional infrastructure management approaches, like manual tracking and oversight, are simply not adequate in these dynamic, ever-changing environments.  

Increase in Data Retention Requirements – The volume of events and alerts being generated through performance monitoring is growing at an exponential rate. Furthermore, the growing number of APIs, IOT devices, mobile applications and digital and/or machine users is driving service ticket volumes through the roof. This has made manual analysis and reporting far too complex and cumbersome.

Demand for Faster Response Time – The more enterprises digitize their business, the more quickly infrastructure problems must be addressed. User expectations have evolved thanks to the consumerization of technology, which is driving the demand for faster reactions to IT events (whether actual or perceived). This is compounded when the issue in question affects user experience.

More/Expanding Computing Power – Given how easy it has become to adopt cloud infrastructure and third party services has empowered individual lines of business (LOB) to develop their own IT applications and solutions. As a result, both budget and control have moved from the center of IT to the very edges of the network, driving the rollout of more computing power.

Influence and Power of Developers – In modern DevOps, programmers are taking more responsibility for monitoring at the application level, however, responsibility for the interaction between services, applications and infrastructure, as well as accountability for the overall health and function of the IT ecosystem still lies at the feet of core IT. As digital businesses are becoming more complex, IT Ops is taking on more responsibility.

Digital transformation is something organizations in every industry and across the entire globe are striving for. AIOps could very well hold the key to success. Power your AIOps with the right solution. Click here to download your free 30-day trial of Ayehu today.

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5 Ways to Adopt IT Automation Without Breaking the Bank

It’s been a long-held belief in the business world that IT automation projects are costly endeavors. The good news is they don’t have to be. In fact, with the right solution in place, you can easily streamline your IT operations to actually save your business money in the long run. Here are 5 ways that you can develop, implement and deploy IT automation projects for your organization in a way that is cost effective and efficient.

Choose the right tool for your needs. You may think this is easier said than done, but it’s not. The key is to apply the 80/20 rule – that is, beware of IT automation tools that you may only use 20% of the time, but that require 80% of your time to make them work. Instead, select an IT automation tool that allows you to focus on the specific pain points of your particular business, gain quick wins, and manage projects of any size. Finally, make sure the tool is scalable to be able grow as your business needs change.

Take a modular solution approach. Another cost effective way to manage IT automation for your organization is to break each project into individual modules, and then implement each of those modules as needed. This also makes the project more manageable and easier to monitor.

Use an IT automation platform that is easy to use and simple to operate. Tools that are complex and difficult to learn and adapt to mean an added expense for your business, both in terms of the time of deployment and the training it will take to bring staff up to speed with the new process. When evaluating IT process automation tools, make sure that you select one that will be easy to implement and simple enough for everyone on your team to learn and use.

Select a platform that offers pre-packaged workflow templates, integration packs and out-of-the-box functionality. Again, when it comes to running a successful business, time is money. If your IT personnel has to spend hours, days and weeks writing tedious scripts, then you’re losing money. IT automation should be about saving time and improving efficiency. When you can leverage already designed workflows and other standard pre-packaged features, you’ll be able to achieve this goal more effectively.

Prepare your team. The last step for managing an affordable IT automation project is to implement adequate training to your team and bringing the right people on board to manage the project effectively. Determine what skills are needed to get the job done correctly and in the most efficient manner possible, and then set about lining up the right people to handle the job.

It’s time we dispel the myth that IT automation has to be a huge expense, making it out of the reach of small to mid-size businesses. To the contrary, when you approach your IT automation projects from the right direction, with knowledge of what to look for in a platform, and you adequately plan and prepare the right personnel for the job, it can easily be managed within just about any budget. The end result, a savings across your entire organization, will be well worth it in the end.

Want to make your IT automation project a success without breaking the bank? Give Ayehu a try today for FREE.
eBook: 10 time consuming tasks you should automate

IT service management from a different perspective

To date, IT Service Management has consistently been viewed as simply part of the IT infrastructure library (ITIL) processes. However, with the looming shift of IT operations from fragmented services to a more end-to-end, service-driven approach, the concept of ITSM is poised to play an increasingly critical role in business operations. In order to successfully navigate this shift toward service, IT professionals must essentially rethink what this practice is really about and how it will serve their organizations going forward.

The Original Intention of IT Service Management

When it was first developed, IT Service Management was intended to bring a more unified approach to how IT technology services were integrated within the organization as a whole. Rather than managing individual components, ITSM focused on developing a collection of best practice processes (ITIL) and using these best practices to deliver end-to-end services. Organizations would conduct ITSM audits which analyzed things such as ROI, budget adherence, and the effectiveness of communication and identifying and evaluating risk. The purpose was to identify areas that needed improvement so that IT services could be better honed to benefit the entire organization.

What’s missing?

While ITSM is still a concrete practice, in order to be truly effective it must evolve along with the changes of IT as a whole. What’s missing from the original concept of ITSM is the end-user – the customer. Internal processes may have been improved significantly, but if these improvements don’t translate to the customer, it’s not a true victory.

How can IT professionals change their perspective of IT Service Management?

In order to get the most out of ITSM, people must begin to shift their view from strictly internal to also include external benefit. The easiest way to do this is to simply drop the “IT” from ITSM and replace it with automation. This essentially expands the benefit of ITSM from the internal operations of the enterprise to also improve the customer experience through the delivery of faster outcomes, higher quality service and at a much more attractive price. Internal processes are streamlined and made more efficient, while external service also improves. It’s a win-win.

If businesses are going to be successful in the future, they must leverage new and changing technology to truly deliver the unique and unparalleled experiences that their customers are seeking. Adjusting the concept of ITSM to incorporate intelligent automation into the mix will accomplish this goal, providing the competitive advantage needed to thrive in the coming years.

Experience how ITSM automation can be a game changer by downloading your free 30-day trial of Ayehu today.

5 Ways to level up your service desk using it process automation